redo medley_db, ikala, and guitarset create_input_data functions to h…

…ave more stable dataset division.

basic_pitch/data/datasets/guitarset.py

@@ -136,17 +136,19 @@ def create_input_data(
     if seed:
         random.seed(seed)
 
-    def determine_split() -> str:
-        partition = random.uniform(0, 1)
-        if partition < validation_bound:
+    def determine_split(index: int) -> str:
+        if index < len(track_ids) * validation_bound:
             return "train"
-        if partition < test_bound:
+        elif index < len(track_ids) * test_bound:
             return "validation"
-        return "test"
+        else:
+            return "test"
 
     guitarset = mirdata.initialize("guitarset")
+    track_ids = guitarset.track_ids
+    random.shuffle(track_ids)
 
-    return [(track_id, determine_split()) for track_id in guitarset.track_ids]
+    return [(track_id, determine_split(i)) for i, track_id in enumerate(track_ids)]
 
 
 def main(known_args: argparse.Namespace, pipeline_args: List[str]) -> None:

basic_pitch/data/datasets/ikala.py

@@ -138,21 +138,17 @@ def process(self, element: List[str], *args: Tuple[Any, Any], **kwargs: Dict[str
 def create_input_data(train_percent: float, seed: Optional[int] = None) -> List[Tuple[str, str]]:
     assert train_percent < 1.0, "Don't over allocate the data!"
 
-    # Test percent is 1 - train - validation
-    validation_bound = train_percent
-
     if seed:
         random.seed(seed)
 
-    def determine_split() -> str:
-        partition = random.uniform(0, 1)
-        if partition < validation_bound:
-            return "train"
-        return "validation"
-
     ikala = mirdata.initialize("ikala")
+    track_ids = ikala.track_ids
+    random.shuffle(track_ids)
+
+    def determine_split(index: int) -> str:
+        return "train" if index < len(track_ids) * train_percent else "validation"
 
-    return [(track_id, determine_split()) for track_id in ikala.track_ids]
+    return [(track_id, determine_split(i)) for i, track_id in enumerate(track_ids)]
 
 
 def main(known_args: argparse.Namespace, pipeline_args: List[str]) -> None:

basic_pitch/data/datasets/medleydb_pitch.py

@@ -136,22 +136,17 @@ def process(self, element: List[str], *args: Tuple[Any, Any], **kwargs: Dict[str
 def create_input_data(train_percent: float, seed: Optional[int] = None) -> List[Tuple[str, str]]:
     assert train_percent < 1.0, "Don't over allocate the data!"
 
-    # Test percent is 1 - train - validation
-    validation_bound = train_percent
-
     if seed:
         random.seed(seed)
 
-    def determine_split() -> str:
-        partition = random.uniform(0, 1)
-        if partition < validation_bound:
-            return "train"
-        return "validation"
-
     medleydb_pitch = mirdata.initialize("medleydb_pitch")
-    medleydb_pitch.download()
+    track_ids = medleydb_pitch.track_ids
+    random.shuffle(track_ids)
+
+    def determine_split(index: int) -> str:
+        return "train" if index < len(track_ids) * train_percent else "validation"
 
-    return [(track_id, determine_split()) for track_id in medleydb_pitch.track_ids]
+    return [(track_id, determine_split(i)) for i, track_id in enumerate(track_ids)]
 
 
 def main(known_args: argparse.Namespace, pipeline_args: List[str]) -> None:

tests/data/test_medleydb_pitch.py

@@ -54,7 +54,7 @@ def test_medleydb_pitch_invalid_tracks(tmpdir: str) -> None:
 def test_medleydb_create_input_data() -> None:
     data = create_input_data(train_percent=0.5)
     data.sort(key=lambda el: el[1])  # sort by split
-    tolerance = 0.05
+    tolerance = 0.01
     for _, group in itertools.groupby(data, lambda el: el[1]):
         assert (0.5 - tolerance) * len(data) <= len(list(group)) <= (0.5 + tolerance) * len(data)